In this tutorial we are starting to build a single layer neural network with neurolab and Python.
Here's a breakdown of the process:
- we use a simple dataset that has been used previously in this series
- separate it into features and labels
- we inspect it (with the help of a scatter plot)
- set the minimum and maximum values for each input dimension
- set the value for the output neuron
- define the neural net architecture
- we train it on the dataset for 100 epochs with a learning rate of 0.03
- we do some more plotting
- test the neural net on new data.
If you want to make some sense out of what I am saying here, please see the video below :)
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Cristi Vlad Self-Experimenter and Author
Dude, I love your content. You make this stuff seem so accessible... please keep it up!
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Nice. I've been looking for a python based neural network vids. I'm into deep learning but a complete utter newbie myself.
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Well, if you start watching the series and do encounter issue, please let me know. Other than that, enjoy!
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posting is very useful for me, thanks @cristi have shared a very good post, it makes me my mind deeper.
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Nice post
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nice post, I gain more knowledge for your post, thanks for sharing knowledge master. I'm newbie programmer..:)
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